About a-team Marketing Services

A-Team Insight Blogs

Risklab Centralises Risk Data Management with Xenomorph TimeScape

Subscribe to our newsletter

Risklab, the investment and risk solutions specialist within Allianz Global Investors, has implemented Xenomorph’s TimeScape to provide a dynamic risk data management platform that can support the risk services it operates on behalf of its institutional clients.

The company considered a number of data management solutions before selecting Xenomorph’s TimeScape analytics and data management system. The company cites TimeScape’s its flexible, object-oriented model and user-friendly application programme interfaces, which make it quick to model data, add new instruments and structures, and create dynamic risk reports and strategies. The software was implemented earlier this year and is now in full production.

According to Brian Sentance, CEO of Xenomorph, “Risklab was pulling together data from a variety of databases and spreadsheets for analysis, but it was hard work. It needed a central database and the ability to validate, control and ensure consistency of data. It also needed tools that could be used by quants to help them create strategies. This played to our key strengths in data management for risk. TimeScape supports all kinds of data from reference data to real-time data and can be easily integrated with pricing models, calculation engines such as MathWorks’ Matlab and vendor risk engines.” Risklab has an established relationship with IBM’s Algorithmics for the supply of risk management software.

Commenting on Risklab’s use of TimeScape, director Bernhard Brunner, says: “Compared with relational databases, TimeScape’s intuitive object-oriented data model has allowed our financial engineering team to quickly implement new strategies with little or no programming, making it even easier to keep up with ever-changing client requirements.”

Sentance says productivity and resulting time to market are key benefits of TimeScape, but he also points to the software’s object-oriented data model and visual front end that allow both IT and business users to understand and analyse risk data. “Risk engine and pricing model vendors focus on calculations and assume data is perfect, but that is not always the case. Risk managers spend time validating data, so there is a pragmatic need for high-quality and consistent underlying data for risk analyses and model creation. This is our sweet spot,” he says.

Risklab is not alone in its use of Xenomorph, which also names Rabobank, Insight Investment and Société Générale Securities Services among its customers. The company’s recent geographic expansion has netted clients in South America, India and Scandinavia, and added to existing bases in the UK, North America and Asia-Pacific, while product development will soon deliver a version of TimeScape that is dedicated to data management for risk.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Strategies and solutions for unlocking value from unstructured data

Unstructured data accounts for a growing proportion of the information that capital markets participants are using in their day-to-day operations. Technology – especially generative artificial intelligence (GenAI) – is enabling organisations to prise crucial insights from sources – such as social media posts, news articles and sustainability and company reports – that were all but...

BLOG

Challenges of the New Regulatory Landscape: Data Management Summit London Preview

The regulatory landscape for financial institutions has rarely been in greater flux than now, placing new challenges on the technology and data that will be critical to satisfying the requirements of overseers. While digital innovations are offering organisations the opportunity to meet their compliance obligations with greater accuracy and efficiency, they are also encouraging regulators...

EVENT

AI in Capital Markets Summit London

The AI in Capital Markets Summit will explore current and emerging trends in AI, the potential of Generative AI and LLMs and how AI can be applied for efficiencies and business value across a number of use cases, in the front and back office of financial institutions. The agenda will explore the risks and challenges of adopting AI and the foundational technologies and data management capabilities that underpin successful deployment.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...